Hydraulic models in stream restoration

Water boards perform stream restoration projects mainly to restore ecology. Hydrodynamic modelling is an important part of those restoration projects, mainly to forecast future water levels and flood risk. In Dutch stream restoration projects, it is very common to use one-dimensional Sobek software for hydrodynamic modelling. Still, though monitoring of stream restoration projects is scarcely performed, it is a common belief that hydraulic forecasts are not always optimal. The general assumption is that multi-dimensional models can improve upon the predictions made with the one-dimensional model.
This research makes a comparison between modelling stream restoration projects in their design phase with one-dimensional Sobek software compared to two-dimensional Delft3D FM software. The Delft3D FM software was specifically selected out of the two-dimensional models available, because of its flexible grid. This means both spacing and shape of the grid can vary, which is especially useful in modelling meandering streams.
The objective of the research was: to determine if modelling stream restoration projects, in their design phase, with a two-dimensional (Delft3D FM) compared to a one-dimensional (Sobek) model has advantages in forecasting water levels and developments in morphology and vegetation. To investigate this, two restoration projects were modelled, one in the Lunterse beek and one in the Tungelroyse beek. Both projects were traditional stream restoration projects (re-meandering projects).
For the stream restoration project analysed in the Lunterse beek two models were set-up, a Sobek model and a Delft3D FM model. Both models were set-up for the period shortly after restoration and stationary discharge scenarios were used as model forcing. A comparison between simulated water levels and observed water levels showed that the one-dimensional model performed better than the two-dimensional model for this particular situation. It was also found that the water level simulations with the Delft3D FM model could improve if lower roughness values were selected or if the bed level interpolation method was changed though, which was not the case for the Sobek model. It was found that differences in output between the models were likely caused by differences in bathymetry and experience in working with the models.
For the stream restoration project performed in the Tungelroyse beek, a Delft3D FM model was set-up. Again, the period shortly after restoration was modelled using stationary discharge scenarios as forcing for the model. Performance of water level forecasts improved compared to the Delft3D FM model of the Lunterse beek. However, it was concluded that advantages of a two-dimensional model over a one-dimensional model will likely not come from water level forecasts since the water levels simulated with the Sobek model are already accurate. It is expected that the two-dimensional model can list equally good results though if more experience is gained with two-dimensional modelling in stream restoration projects.
Forecasts in morphological developments were made based upon output of the Delft3D FM models. First the locations where transport can be expected were determined using the Shields parameter and the critical Shields parameter. After that flow velocity and flow direction maps were made for the most important discharge scenarios. For the Lunterse beek these maps were qualitatively compared to monitored quantitative developments in bed level. The maps created with the high uniform discharge scenarios (T100, T10 and T1) showed good correspondence to monitored developments, while the lower discharge scenarios (T0.05 and T0.005) showed some correspondence looking into bed erosion and sedimentation. It was found that the monitored discharge for the given period was between the discharge used as forcing for the T0.05 and T0.005 scenarios. The bank erosion that was monitored in the field could not be explained by these scenarios. An explanation for this can be that water levels are overestimated in the model, wherefore flow velocities are underestimated for equal discharges.
The flow velocity and flow direction maps made for the Tungelroyse beek agreed with qualitative developments monitored with respect to morphology. However, no quantitative measurements were performed of bed level developments. Therefore, agreement between forecasts made with the models and developments encountered in reality could not be proven. In the end it was concluded that there might be benefits of a two-dimensional model with respect to forecasting morphological developments after stream restoration in its design phase, but this could not be proven in this research.
To make forecasts about expected developments in vegetation, flow velocity output of the Delft3D FM models was used. In the literature it was found that more vegetation can be expected for locations with low flow velocities and less vegetation if flow velocities are high. Though developments in vegetation depend on many other factors, it was found that forecasts corresponded quite well to monitored developments in vegetation for some scenarios. Validation was performed for the Lunterse beek by using a high resolution aerial image and for the Tungelroyse beek using a Normalized Difference Vegetation Index (NDVI) map. It has to be noted though that in-stream vegetation developments could not be validated, while these are often very important for water boards.
Finally it was concluded that using a two-dimensional Delft3D FM model in the design phase of stream restoration projects to make forecasts in vegetation development might be beneficial. Using flow velocity output of the two-dimensional model to base these forecasts upon gave good results for a few discharge scenarios for both streams. There might also be a benefit in two-dimensional modelling with respect to making forecasts in morphological developments, however this is only partly supported by this research. Finally, it became clear that advantages of a two-dimensional model compared to one-dimensional model are likely not present in water level forecasts since the one-dimensional model already performs very well. It is expected though, that the water level forecasts made with the two-dimensional model can be improved by gathering more experience. This should eventually lead to water level forecasts that are just as accurate for the two-dimensional model as for the one-dimensional model.